Phylogeographic analysis of hepatitis A virus in Russia

1. Phylogeographic analysis of hepatitis A virus in Russia

MSc Program
Phylogeographic analysis of
hepatitis A virus in Russia
Student: Alevtina Koreshova
Research Advisor: Georgii Bazykin
Co-Advisor: Alexey Neverov
January, 2019

2. Introduction

Hepatitis A virus (HAV)
• is a positive-stranded RNA virus, 7.5 kb genome
• causes acute hepatitis in adults
• spreads via fecal-oral route
• vaccination is very effective, but nearly nobody does it
• comprises 6 genotypes, from which I and III are most
frequent in humans and are both divided into A and B
subgenotypes
• genotyping is carried out on short variable fragments
• in Russia, IA and IIIA subgenotypes predominate
• has low mutation rate ≈ 1.99 x 10−4 (Kulkarni et al.,
2009)
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3. Aim and objectives

The aim of the work is to reconstruct the phylogenetics,
geographic structure and migration events of HAV in
Russia.
The hypothesis is that IIIA subgenotype originates from
India while IA is expanding from Europe.
Objectives:
• Phylogeographic analysis using Bayesian approach
(BEAST)
• Phylogeographic analysis with ML approach (augur)
and GenGis
• Obtaining full genomes of HAV
• Have fun with full genomes
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4. The dataset

Central Research Institute of Epidemiology kindly provided us with
the unique collection of HAV isolates obtained all over Russian
Federation and CIS countries.
Samples (more than 500 isolates) were collected from 1999 to 2015
and characterized by one of the two most variable fragments of HAV
genome (VP1 and 2C regions) or by both of them.
The dataset includes 124 unique sequences of 2C/3A region, length
≈ 650 bp, and 217 sequences of VP1/2A region, length ≈ 400 bp.
For each sample, date and location of collection is indicated.
Whole-genome sequences of HAV from GenBank were used
(accession numbers KC182588, KC182589, HM769724, LC049342,
LC049339, LC049338, AB909123, AB623053, JQ655151,
AB973400, FJ360735, FJ360734, FJ360733, FJ360732, FJ360731,
FJ360730, AB279734, AB279733, AB279732).
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5. Methods

Software:
MEGA – alignment, tree reconstruction
IQTree – model selection
BEAST – phylogeography, model selection
Spread3 – visualization of phylogeography
Chelper – primer design for sequencing of whole genomes
Planned:
GenGis – estimating directions of migration
Augur – phylogeography based on ML, not Bayes
This python package which name I don’t know – geographic
clusterization
Whole genome sequencing will be performed with Mi-seq
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6. BEAST and VEME2018

The 23rd International
Workshop on Virus
Evolution and Molecular
Epidemiology (VEME2018)
was hosted in Berlin,
Germany. It was devoted to
phylogenetic inference and
BEAST.
Markov chain Monte Carlo
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7. Results

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8. Results: IA phylogeography

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9. Results: IIIA phylogeography

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10. Discussion and problems

• Sampling issues
• Uncertainty in time and place of sample
collection (current solution – setting random
jitter in BEAST)
• Low mutation rate => low resolution
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11. Plans

• Verify BEAST results with other approaches
(augur, GenGis)
• Obtain whole genomes of HAV
• Analyze the whole genomes and add partial
sequences from Genbank if possible
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12. Conclusions (obtained, desired)

So far, the results of BEAST estimation of
phylogeography agree with literature data
Desired :
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13. Acknowledgements

List of colleagues who considerably contributed in
the research.
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